3D GEOMETRIC MODELING AND 3D VIDEO CONTENT CREATION

• US 20100074532A1
• Filed: 11/20/2007
• Published: 03/25/2010
• Est. Priority Date: 11/21/2006
• Status: Active Grant

• Current Assignee: Mantis Vision, Ltd.
• Original Assignee: Mantis Vision, Ltd.
• Inventors: Bittan, Gur Arieh, Gordon, Eyal
• Granted Patent: US 8,538,166 B2
• Time in Patent Office: Days
• US Class Current: 382/203
• CPC Class Codes: G01B 11/25 by projecting a pattern, e.g. one or more lines, moiré fringes on the object G01B11/255 takes precedence ; image analysis for depth or shape recovery G06T7/50
• CPC Class Codes: G01B 11/2513 with several lines being projected in more than one direction, e.g. grids, patterns
• CPC Class Codes: G01C 11/025 by scanning the object
• CPC Class Codes: G06T 15/205 Image-based rendering
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/20228 Disparity calculation for image-based rendering
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/536 from perspective effects, e.g. by using vanishing points
• CPC Class Codes: G06V 10/145 Illumination specially adapted for pattern recognition, e.g. using gratings

Abstract

A system, apparatus and method of obtaining data from a 2D image in order to determine the 3D shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising: (a) providing a predefined set of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation; (b) providing a coded light pattern comprising multiple appearances of said feature types; (c) projecting said coded light pattern on said objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features; (d) capturing a 2D image of said objects having said projected coded light pattern projected thereupon, said 2D image comprising reflected said feature types; and (e) extracting: (i) said reflected feature types according to the unique bi-dimensional formations; and (ii) locations of said reflected feature types on respective said epipolar lines in said 2D image.

Claims

1-111. -111. (canceled)

112. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a predefined set of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

providing a coded light pattern comprising multiple appearances of said feature types;

projecting said coded light pattern on said objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

capturing a 2D image of said objects having said projected coded light pattern projected thereupon, said 2D image comprising reflected said feature types; and

extracting;

a) said reflected feature types according to the unique bi-dimensional formations; and

b) locations of said reflected feature types on respective said epipolar lines in said 2D image.

113. The method according to claim 112, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

114. The method according to claim 113, further comprising providing a 3D point cloud by a compilation of the 3D spatial coordinates.

115. The method according to claim 114, further comprising processing the 3D point cloud to form a 3D surface.

116. The method according to claim 112, further comprising adding texture data of the objects.

117. The method according to claim 112, further comprising providing the coded light pattern as one or more of the following:

a) a repeating periodic pattern; and

b) a non-periodic pattern.

118. The method according to claim 112, further comprising projecting the coded light pattern such that each of the feature types appears at most once on one or more predefined sections of the distinguishable epipolar lines.

119. The method according to claim 118, further comprising providing the entire length of epipolar lines in the 2D image within the predefined sections of the epipolar lines.

120. The method according to claim 118, further comprising providing the predefined sections as sections of the length of the epipolar lines in the 2D image.

121. The method according to claim 112, further comprising projecting the coded light pattern at an angle in relation to the epipolar lines in accordance with the parameters of a Sin⁻

1(P/YC) equation.

122. The method according to claim 112, wherein extracting the reflected feature types according to the unique bi-dimensional formations comprises determining:

a) elements that comprise said reflected feature types; and

b) epipolar distances between said elements of said reflected feature types.

123. The method according to claim 122, further comprising providing the elements of the reflected feature types as bi-dimensional light intensity formations on a pixel area of a sensor.

124. The method according to claim 123, further comprising identifying the bidimensional light intensity formations by locating critical points of light intensity among adjacent sampled pixel values.

125. The method according to claim 122, further comprising providing the elements as predefined values.

126. The method according to claim 122, further comprising expressing locations of the elements as two-dimensional coordinates in the 2D image.

127. The method according to claim 122, further comprising providing the epipolar distances between the elements as one or more of the following:

a) constant distances; and

b) varying distances.

128. The method according to claim 112, further comprising providing a spectral encoding within the unique bi-dimensional formation.

129. The method according to claim 112, further comprising capturing the 2D image at each of successive time frames.

130. The method according to claim 129, further comprising determining, for each of the 2D images, corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines for each of the 2D images.

131. The method according to claim 130, further comprising forming a video stream providing 3D motion capture by means of the 3D spatial coordinates.

132. The method according to claim 131, further comprising computing the 3D spatial coordinates substantially in real-time to provide a substantially real-time video stream of the 3D motion capture.

133. The method according to claim 112, further comprising generating the bi-dimensional coded light pattern by superimposing a plurality of values on a predefined pattern, said values derived from one or more of the following:

a. Debruijn sequences;

b. Perfect Maps;

c. M-Arrays; and

d. Pseudo-random codes.

134. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a predefined set of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

providing a coded light pattern comprising multiple appearances of said feature types;

projecting said coded light pattern on said objects at an angle in relation to said epipolar lines, said angle being in accordance with a determined limiting distance between said distinguishable epipolar lines;

capturing a 2D image of said objects having said projected coded light pattern projected thereupon, said 2D image comprising reflected said feature types; and

extracting;

a) said reflected feature types according to the unique bidimensional formations; and

b) locations of said reflected feature types on respective said epipolar lines in said 2D image.

135. The method according to claim 134, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

136. An apparatus configured to obtain data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said apparatus comprising:

a predefined set of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

a coded light pattern comprising multiple appearances of said feature types;

a projector configured to project said coded light pattern on said objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

an imaging device configured to capture a 2D image of said objects having said projected coded light pattern projected thereupon, said 2D image comprising reflected said feature types; and

an image processing device configured to extract;

a) said reflected feature types according to the unique bi-dimensional formations; and

b) locations of said reflected feature types on respective said epipolar lines in said 2D image.

137. The apparatus according to claim 136, wherein the locations on the respective epipolar lines of the reflected feature types determine corresponding 3D spatial coordinates of the objects.

138. The apparatus according to claim 136, wherein the projector is further configured such that the projecting of the coded light pattern is at an angle in relation to the epipolar lines in accordance with the parameters of a Sin⁻

1(P/YC) equation.

139. The apparatus according to claim 136, further configured to move in three-dimensions in relation to the objects during the imaging of said objects.

140. The apparatus according to claim 136, further configured to capture the images of the objects that are moving in three dimensions in relation to said apparatus.

141. A method of obtaining data from a 2D (two-dimensional) video sequence, comprising two or more frames, each frame being a 2D image, in order to determine the 3D (three-dimensional) shape of moving objects appearing in said 2D video sequence, each frame having distinguishable epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said coded light pattern on said moving objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

capturing said 2D video sequence having said moving objects having said projected coded light pattern projected thereupon, said 2D video sequence comprising reflected said feature types; and

extracting;

a) said reflected feature types according to the unique bi-dimensional formations; and

b) locations of said reflected feature types on respective said epipolar lines.

142. The method according to claim 141, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

143. The method according to claim 141, further comprising providing, for each projection, each of the feature types appears at most once on one or more predefined sections of the distinguishable epipolar lines.

144. An apparatus configured to obtain data from 2D (two-dimensional) video sequence, comprising two or more frames, each frame being a 2D image, in order to determine the 3D (three-dimensional) shape of moving objects appearing in said 2D video sequence, each frame having distinguishable epipolar lines, said apparatus comprising:

a bi-dimensional coded light pattern having a plurality of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

a projector configured to project said coded light pattern on said moving objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

an imaging device configured to capture said 2D video sequence having said moving object having said projected coded light pattern projected thereupon, said 2D video sequence comprising reflected said feature types; and

an image processing device configured to extract;

a) said reflected feature types according to the unique bi-dimensional formations; and

b) locations of said reflected feature types on respective said epipolar lines.

145. The apparatus according to claim 144, wherein the locations of the reflected feature types on the respective epipolar lines determine corresponding 3D spatial coordinates of the objects.

146. A method of obtaining distance data from a scene comprising one or more objects, the method comprising:

projecting a bidimensional coded light pattern having a plurality of feature types onto said scene such that each feature of said light pattern is reflected from a different respective reflection location in said scene, giving rise to a reflected feature, said feature types being distinguishable according to a unique bi-dimensional formation, said projecting performed such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

capturing a 2D (two-dimensional) image of said scene comprising the reflected features;

determining for each said reflected feature appearing in said 2D image;

a) a respective feature type according to said unique bi-dimensional formation; and

b) a location of said each reflected feature on the respective epipolar line; and

deriving for said each reflected feature, in accordance with the respective determined feature type and with the respective determined location on said respective epipolar line, a respective distance of a respective associated reflection location.

147. The method according to claim 146, further comprising providing a 3D (three-dimensional) geometric shape of the one or more objects by a compilation of the respective distances.

148. The method according to claim 146, wherein determining of the respective feature type and the respective epipolar line comprises effecting a correspondence between the respective determined feature type in the 2D image and the location of the same feature type in a projected pattern.

149. A system configured to obtain scene data from a target scene, the system comprising:

a pattern-projecting apparatus operative to project a bi-dimensional coded light pattern having a plurality of feature types onto said scene such that each feature reflects from a respective reflection location, giving rise to a reflected feature, said feature types being distinguishable according to a unique bi-dimensional formation, wherein said coded light pattern are projected such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

an image capture apparatus operative to capture a 2D (two-dimensional) image of said scene comprising the reflected features; and

an image processing element operative, for each said reflected feature of said 2D image, to;

i) determine, for said each reflected feature;

A. a feature type according to said unique bi-dimensional formation; and

B. a location of said each reflected feature on the respective epipolar line;

and

ii) derive, for each said reflected feature, in accordance with the respective determined feature type and with the respective determined location on the respective epipolar line, a respective distance of a respective associated reflection location.

150. A method of determining the 3D (three-dimensional) shape of imaged objects appearing in at least two obtained 2D (two-dimensional) images, said obtained images related to each other by defined epipolar fields, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said coded light pattern on said imaged objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

capturing a first 2D image of said imaged objects;

capturing a second 2D image of said imaged objects;

selecting a pixel area PX1 of said first 2D image, the content appearing on PX1 being constrained to appear on a specific epipolar line EPm in said second 2D image;

finding said content of said pixel area PX1 in said second 2D image along said epipolar line EPm; and

determining locations of appearances of said content of said pixel area PX1 between said first and second 2D images.

151. The method according to claim 150, further comprising determining corresponding 3D spatial coordinates of the imaged objects by means of the locations of the appearances of the content of the pixel area PX1.

152. The method according to claim 150, further comprising extracting for each of said 2D images, independently, reflected feature types, said feature types being reflected from the imaged objects, according to the unique bi-dimensional formations and the feature type locations on the respective epipolar lines.

153. The method according to claim 150, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types, said feature types being reflected from the imaged objects, on the respective epipolar lines.

154. A method of determining the 3D (three-dimensional) shape of imaged objects appearing in at least two obtained 2D (two-dimensional) images, said obtained images related to each other by defined epipolar fields, each epipolar field comprising one or more epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said coded light pattern on said imaged objects at an angle in relation to at least one of said epipolar fields, said angle being in accordance with a determined limiting distance between distinguishable epipolar lines;

capturing a first 2D image of said imaged objects;

capturing a second 2D image of said imaged objects;

selecting a pixel area PX1 of said first 2D image, the content appearing on PX1 being constrained to appear on a specific epipolar line EPm in said second 2D image;

finding said content of said pixel area PX1 in said second 2D image along said epipolar line EPm; and

determining locations of appearances of said content of said pixel area PX1 between said first and second 2D images.

155. The method according to claim 154, further comprising determining corresponding 3D spatial coordinates of the imaged objects by means of the locations of the appearances of the content of the pixel area PX1.

156. The method according to claim 154, further comprising extracting for each of said 2D images, independently, reflected feature types, said feature types being reflected from the imaged objects, according to the unique bi-dimensional formations and the feature type locations on the respective epipolar lines.

157. The method according to claim 154, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types, said feature types being reflected from the imaged objects, on the respective epipolar lines.

158. An apparatus configured to determine the 3D (three-dimensional) shape of imaged objects appearing in two or more obtained 2D (two-dimensional) images, said two or more 2D images being obtained from at least two imaging devices, said two or more 2D images being related to each other by defined epipolar fields, said apparatus comprising:

a bi-dimensional coded light pattern having a plurality of types of features, giving rise to feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

a projector configured to project said coded light pattern on said imaged objects such that the distance between epipolar lines associated with substantially identical features is less than the distance between corresponding locations of two neighboring features;

a first imaging device configured to capture a first 2D image of said imaged objects;

a second imaging device configured to capture a second 2D image of said imaged objects;

an image processing device configured to;

a) select a pixel area PX1 of said first 2D image, the content appearing on said pixel area PX1 being constrained to appear on a specific epipolar line EPm in said second 2D image;

b) find said content of said pixel area PX1 in said second 2D image along said epipolar line EPm; and

c) determine locations of appearances of said content of said pixel area PX1 between said first and second 2D images.

159. The apparatus according to claim 158, wherein the locations of the appearances of the content of the pixel area PX1 determine corresponding 3D spatial coordinates of the imaged objects.

160. The apparatus according to claim 158, wherein the image processing device is further configured to extract in each image, independently, the reflected feature types, said feature types being reflected from the imaged objects, according to the unique bi-dimensional formations and the feature type locations on the respective epipolar lines.

161. The apparatus according to claim 158, wherein the locations of the reflected feature types, said feature types being reflected from the imaged objects, on the respective epipolar lines determine corresponding 3D spatial coordinates of said imaged objects.

162. The apparatus according to claim 158, further configured to move in three dimensions in relation to objects during the imaging.

163. The apparatus according to claim 158, further configured to capture the 2D images of objects, said objects moving in three dimensions in relation to said apparatus.

164. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of feature types, each of said feature types being distinguishable according to a unique bi-dimensional formation;

providing the inverse of said bi-dimensional coded light pattern, giving rise to an inverse coded light pattern;

projecting said coded light pattern and said inverse coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said projected coded light pattern being projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having said inverse coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

obtaining a resultant image from the subtraction of said second 2D image from said first 2D image; and

extracting said reflected feature types according to the unique bi-dimensional formations and the feature type locations on respective said epipolar lines in said resultant image.

165. The method according to claim 164, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

166. The method according to claim 164, further comprising projecting the light patterns by one or more of the following:

a) temporally;

b) with differing spectral values of light; and

c) with differing polarization.

167. The method according to claim 164, further comprising capturing the first 2D image and second 2D images temporally, giving rise to temporal imaging.

168. The method according to claim 167, further comprising carrying out the temporal imaging over non-uniform time intervals.

169. The method according to claim 164, further comprising capturing the first and second 2D images simultaneously by using spectral differentiation.

170. The method according to claim 164, further comprising carrying out the extraction of the feature types in the resultant image by determining intensity values of sample points.

171. An apparatus configured to obtain data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said apparatus comprising:

a predefined set of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

a bi-dimensional coded light pattern comprising multiple appearances of the feature types;

an inverse bi-dimensional coded light pattern comprising multiple appearances of the inversed feature types;

a projector configured to project said bi-dimensional coded light pattern and said inverse bi-dimensional light pattern on said objects;

a first imaging device configured to capture a first 2D image of said objects, having said projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types;

a second imaging device configured to capture a second 2D image of said objects, having said inverse coded light pattern projected thereupon, said second 2D image comprising reflected said feature types; and

an image processing device configured to;

i) obtain a resultant image from the subtraction of said second 2D image from said first 2D image; and

ii) extract said reflected feature types according to the unique bi-dimensional formations and the feature type locations on respective said epipolar lines in said resultant image.

172. The apparatus according to claim 171, wherein the feature type locations on the respective epipolar lines determine corresponding 3D spatial coordinates of the objects.

173. A method of obtaining texture data from two 2D (two-dimensional) images, each of said images containing a reflected code used to obtain depth data of imaged objects independently for each 2D image, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation,

providing the inverse of said bi-dimensional coded light pattern, giving rise to an inverse coded light pattern;

projecting said coded light pattern and said inverse coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types,

ii) a second 2D image of said objects, having said inverse coded light pattern projected thereupon, said second 2D image comprising reflected said feature types,

obtaining a resultant image from the addition of said second 2D image with said first 2D image, said resultant image providing texture information of said imaged objects.

174. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

providing the inverse of said bi-dimensional coded light pattern, giving rise to an inverse coded light pattern;

projecting said coded light pattern and said inverse coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having said inverse coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

obtaining a resultant image from the absolute value of the subtraction of said second 2D image from said first 2D image, said resultant image comprising outlines of said reflected feature types; and

extracting said outlines and outline locations on respective said epipolar lines in said resultant image.

175. The method according to claim 174, further comprising determining corresponding 3D spatial coordinates of the objects by means of the outline locations on the respective epipolar lines.

176. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a first bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation and each feature type comprising a plurality of elements having varying light intensity, wherein said plurality of elements comprises non-maximum and non-minimum elements and comprises one or more of the following;

at least one maximum element;

at least one minimum element; and

at least one saddle element;

providing a second bi-dimensional coded light pattern comprising said first bi-dimensional coded light pattern having the one or more maximum and/or minimum inverted elements;

projecting said first bi-dimensional coded light pattern and said second bi-dimensional coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said first projected bi-dimensional coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having said second bi-dimensional coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

obtaining a resultant image from the subtraction of said second 2D image from said first 2D image; and

extracting from said resultant image one or more of the following;

at least one maximum element, at least one minimum element and at least one saddle element, and extracting their locations respective to said epipolar lines in said resultant image.

177. The method according to claim 176, further comprising determining corresponding 3D spatial coordinates of the objects by determining locations of the one or more of the following:

at least one maximum element, at least one minimum element, and at least one saddle element and/or by determining locations of the non-maximum and non-minimum elements on the respective epipolar

178. The method according to claim 176, further comprising determining corresponding 3D spatial coordinates of the objects by determining locations of the one or more of the following:

at least one maximum element, at least one minimum element, and at least one saddle element and/or by determining locations of the non-maximum and non-minimum elements on the respective epipolar lines.

179. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a first bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation and each feature type comprising a plurality of elements having varying light intensity, wherein said plurality of elements comprising non-maximum and non-minimum elements and comprising one or more of the following;

at least one maximum element;

at least one minimum element; and

at least one saddle element;

providing a second bi-dimensional coded light pattern comprising said first bi-dimensional coded light pattern having the one or more maximum and/or minimum inverted elements;

projecting said first bi-dimensional coded light pattern and said second bi-dimensional coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said first projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having said second coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

obtaining a resultant image from the addition of said second 2D image with said first 2D image; and

extracting from said resultant image one or more said non-maximum and non-minimum elements and extracting locations of said non-maximum and non-minimum elements on one or more respective epipolar lines in said resultant image.

180. The method according to claim 179, further comprising determining the corresponding feature types by determining their locations and/or by determining values of the one or more of the following:

at least one maximum element, at least one minimum element, at least one non-maximum element, at least one non-minimum element and at least one saddle element.

181. The method according to claim 179, further comprising determining corresponding 3D spatial coordinates of the objects by determining locations of the one or more of the following:

at least one maximum element, at least one minimum element, and at least one saddle element and/or by determining locations of the non-maximum and non-minimum elements on the respective epipolar

182. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a first bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation and each feature type comprising a plurality of elements having varying light intensity, wherein said plurality of elements comprises non-maximum and non-minimum elements and comprises one or more of the following;

at least one maximum element;

at least one minimum element; and

at least one saddle element;

providing a second bi-dimensional coded light pattern comprising said first bi-dimensional coded light pattern having the one or more maximum and/or minimum inverted elements;

projecting said first bi-dimensional coded light pattern and said second bi-dimensional coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said first projected bi-dimensional coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having said second bi-dimensional coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

obtaining a resultant image from the absolute value of the subtraction of said second 2D image from said first 2D image, said resultant image comprising borderlines of said reflected feature types; and

extracting said borderlines and borderline locations on respective said epipolar lines in said resultant image.

183. The method according to claim 182, further comprising determining corresponding 3D spatial coordinates of the objects by means of the borderline locations on the respective epipolar

185. The method according to claim 182, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

184. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a first bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

providing a second bi-dimensional coded light pattern, different from said first pattern, having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said first coded light pattern and said second coded light pattern on said objects;

capturing;

i) a first 2D image of said objects having said first projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects having said second coded light pattern projected thereupon, said second 2D image comprising reflected said feature types;

extracting, in each image independently, said reflected feature types according to the unique bi-dimensional formations and the feature type locations on respective said epipolar lines; and

comparing regions of epipolar lines in said second 2D image to similar regions along same epipolar lines in said first 2D image to verify feature identities in said first 2D image.

186. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said bi-dimensional coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having ambient light projected thereupon;

obtaining a resultant image from the subtraction of said second 2D image from said first 2D image; and

extracting said reflected feature types and locations of said reflected feature types on respective said epipolar lines in said resultant image.

187. The method according to claim 186, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.

188. A method of obtaining data from a 2D (two-dimensional) image in order to determine the 3D (three-dimensional) shape of objects appearing in said 2D image, said 2D image having distinguishable epipolar lines, said method comprising:

providing a bi-dimensional coded light pattern having a plurality of feature types, each feature type being distinguishable according to a unique bi-dimensional formation;

projecting said coded light pattern on said objects;

capturing;

i) a first 2D image of said objects, having said projected coded light pattern projected thereupon, said first 2D image comprising reflected said feature types; and

ii) a second 2D image of said objects, having uniform light projected thereupon;

obtaining a resultant image from the division of said first 2D image by said second 2D image; and

extracting said reflected feature types and the locations of said reflected feature types on respective said epipolar lines in said resultant image.

189. The method according to claim 188, further comprising determining corresponding 3D spatial coordinates of the objects by means of the locations of the reflected feature types on the respective epipolar lines.